json_assert_paths
Assert JSONPath expressions against JSON (exists/equals/type) — agent self-check.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| assertions | Yes |
Assert JSONPath expressions against JSON (exists/equals/type) — agent self-check.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| assertions | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It only mentions 'agent self-check' without explaining error handling, return format, or whether assertions are silent or produce output. This leaves significant ambiguity for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a single sentence that conveys the core functionality. It is front-loaded and avoids unnecessary words. However, it may be too brief for adequate understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 params, no output schema, no annotations), the description covers the high-level purpose but lacks details on assertion semantics, return values, and error conditions. It is minimally complete but leaves gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not clarify parameter semantics. It mentions JSONPath and assertion types but fails to explain the structure of the assertions array or the meaning of fields like path, type, equals, exists. The description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool asserts JSONPath expressions against JSON data with operations like exists, equals, and type. It distinguishes from similar tools like jsonpath_query by implying assertion rather than querying, but does not explicitly differentiate from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., jsonpath_query for querying, json_equal for direct comparison). The description does not mention use cases, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.
All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.
193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.
Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.